Groupwise successive interference cancellation for block transmission with reception diversity

ABSTRACT

A plurality of data signals are received over an antenna array having a plurality of antenna elements. The data signals are transmitted over a shared spectrum in a wireless communication system. A signal having each of the data signals is received over each antenna element. The plurality of data signals are grouped into a plurality of groups. The received signals of the antenna elements are matched filtered for a first group of the plurality of groups, producing a matched filtered result. Data is jointly detected of the first group using the matched filtered result. An interference correction signal is constructed using the detected data for each antenna element. The interference cancelled result is subtracted from the received signal of each antenna element, producing an interference cancelled result for each antenna element. Data is successively detected for remaining groups using the interference cancelled result for each antenna element.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.10/622,306, filed Jul. 18, 2003, which claims the benefit of U.S.Provisional Application Ser. No. 60/397,361, filed Jul. 19, 2002, whichare incorporated by reference as if fully set forth.

FIELD OF INVENTION

The invention generally relates to wireless communication systems. Inparticular, the invention relates to joint detection of multiple usersignals in a wireless communication system.

BACKGROUND

FIG. 1 is an illustration of a wireless communication system 10. Thecommunication system 10 has base stations 12 ₁ to 12 ₅ which communicatewith wireless transmit/receive units (WTRUs) 14 ₁ to 14 ₃. Each basestation 12 ₁ has an associated operational area where it communicateswith WTRUs 14 ₁ to 14 ₃ in its operational area.

In some communication systems, such as code division multiple access(CDMA) and time division duplex using code division multiple access(TDD/CDMA), multiple communications are sent over the same frequencyspectrum. These communications are typically differentiated by theirchip code sequences. To more efficiently use the frequency spectrum,TDD/CDMA communication systems use repeating frames divided into timeslots for communication. A communication sent in such a system will haveone or multiple associated codes and time slots assigned to it based onthe communication's bandwidth.

Since multiple communications may be sent in the same frequency spectrumand at the same time, a receiver in such a system must distinguishbetween the multiple communications. One approach to detecting suchsignals is matched filtering. In matched filtering, a communication sentwith a single code is detected. Other communications are treated asinterference. To detect multiple codes, a respective number of matchedfilters are used. Another approach is successive interferencecancellation (SIC). In SIC, one communication is detected and thecontribution of that communication is subtracted from the receivedsignal for use in detecting the next communication.

In some situations, it is desirable to be able to detect multiplecommunications simultaneously in order to improve performance. Detectingmultiple communications simultaneously is referred to as jointdetection. Some joint detectors use Cholesky decomposition to perform aminimum mean square error (MMSE) detection or zero-forcing blockequalizers (ZF-BLEs). Other joint detection receivers use fast Fouriertransform based implementations to reduce the complexity further.

Accordingly, it is desirable to have alternate approaches to multi-userdetection.

SUMMARY

A plurality of data signals are received over an antenna array having aplurality of antenna elements. The data signals are transmitted over ashared spectrum in a wireless communication system. A signal having eachof the data signals is received over each antenna element. The pluralityof data signals are grouped into a plurality of groups. The receivedsignals of the antenna elements are matched filtered for a first groupof the plurality of groups, producing a matched filtered result. Data isjointly detected of the first group using the matched filtered result.An interference correction signal is constructed using the detected datafor each antenna element. The interference cancelled result issubtracted from the received signal of each antenna element, producingan interference cancelled result for each antenna element. Data issuccessively detected for remaining groups using the interferencecancelled result for each antenna element.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified illustration of a wireless communication system.

FIG. 2 is a simplified block diagram of a transmitter and a jointdetection group successive interference canceller receiver havingmultiple antenna elements.

FIG. 3 is an illustration of a communication burst.

FIG. 4 is a flow chart for joint detection group successive interferencecanceling for a receiver having multiple antenna elements.

FIG. 5 is a simplified block diagram of a joint detection groupsuccessive interference canceller.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Hereafter, a wireless transmit/receive unit (WTRU) includes but is notlimited to a user equipment, mobile station, fixed or mobile subscriberunit, pager, or any other type of device capable of operating in awireless environment. When referred to hereafter, a base stationincludes but is not limited to a base station, Node-B, site controller,access point or other interfacing device in a wireless environment.

FIG. 2 illustrates a simplified transmitter 26 and receiver 28 using anadaptive combination of joint detection (JD) and group-wise successiveinterference cancellation (GSIC), “GSIC-JD”, where reception diversityis used. In a typical system, a transmitter 26 is in each WTRU 14 ₁ to14 ₃ and multiple transmitting circuits 26 sending multiplecommunications are in each base station 12 ₁ to 12 ₅. A base station 12₁ will typically require at least one transmitting circuit 26 for eachactively communicating WTRU 14 ₁ to 14 ₃. The GSIC-JD receiver 28 may beat a base station 12 ₁, WTRUs 14 ₁ to 14 ₃ or both, although the morecommon implementation is at a base station, where the use of multipleantenna elements is more common. The GSIC-JD receiver 28 receivescommunications from multiple transmitters 26 or transmitting circuits26.

Although GSIC-JD is described in conjunction with the preferredapplication to a slotted CDMA system, such as TDD/CDMA or time divisionsynchronous CDMA (TD-SCDMA), it can be applied to any wireless systemwhere multiple communications share the same frequency band, such asfrequency division duplex (FDD)/CDMA and CDMA 2000.

Each transmitter 26 sends data over a wireless radio channel 30. A datagenerator 32 in the transmitter 26 generates data to be communicatedover a reference channel to a receiver 28. Reference data is assigned toone or multiple codes and/or time slots based on the communicationsbandwidth requirements. A modulation and spreading device 34 spreads thereference data and makes the spread reference data time-multiplexed witha training sequence in the appropriate assigned time slots and codes,for slotted systems. In non-slotted systems, the reference signal maynot be time-multiplexed, such as an almost continuous global pilot. Theresulting sequence is referred to as a communication burst. Thecommunication burst is modulated by a modulator 36 to radio frequency.An antenna 38 radiates the RF signal through the wireless radio channel30 to an antenna array 40 of the receiver 28. The type of modulationused for the transmitted communication can be any of those known tothose skilled in the art, such as direct phase shift keying (DPSK),quadrature phase shift keying (QPSK) or M-ary quadrature amplitudemodulation (QAM).

In slotted systems, a typical communication burst 16 has a midamble 20,a guard period 18 and two data fields 22, 24, as shown in FIG. 3. Themidamble 20 separates the two data fields 22, 24 and the guard period 18separates the communication bursts to allow for the difference inarrival times of bursts transmitted from different transmitters. The twodata fields 22, 24 contain the communication burst's data and aretypically the same symbol length. The midamble 20 contains a trainingsequence.

The antenna array 40 of the receiver 28 receives various radio frequencysignals. The antenna array 40 has P antenna elements 41 ₁ to 41 _(P).The received signals are demodulated by demodulators 42 ₁ to 42 _(P) toproduce baseband signals. The baseband signals are processed, such as bya channel estimation device 44 and a GSIC-JD device 46, in the timeslots and with the appropriate codes assigned to the communicationbursts of the corresponding transmitters 26. The channel estimationdevice 44 uses the training sequence component in the baseband signalsto provide channel information, such as channel impulse responses. Thechannel information is used by the GSIC-JD device 46 to estimate thetransmitted data of the received communication bursts as either hard orsoft symbols.

FIG. 4 is a simplified diagram of a GSIC-JD device 46. For thefollowing, sequences, vectors, and matrices are in boldface and (•)^(H)denotes the complex conjugate transpose operation and (•)^(T) denotesthe real transposition.

K signal bursts are simultaneously active in the same frequency band ofwidth B. The K bursts are separated by their different codes. In a UMTSTDD/CDMA system, the codes may consist of a cell specific scramblingcode and a single or multiple channelization codes. The finitetransmitted data symbol sequence, d^((k)), of length N is per Equation1.d ^((k))=(d ₁ ^((k)) d ₂ ^((k)) . . . d _(N) ^((k)))^(T), d_(n)^((k))εV,i. where k=1, 2, . . . , K and n=1, 2, . . . , N  Equation 1

Each data symbols d_(n) ^((k)) has a duration T_(b) and each datasymbols d_(n) ^((k)) is taken from a complex M-ary set, V, having Mpotential values per Equation 2.a. V={v₁ v₂ . . . v_(M)}  Equation 2

Each data symbol sequence, d^((k)), is spread by the code c^((k)).c^((k)) is per Equation 3.a. c ^((k))=(c ₁ ^((k)) c ₂ ^((k)) . . . , c _(Q) ^((k)))^(T), wherek=1, 2, . . . , K and q=1, 2, . . . , Q  Equation 3

Each code, c^((k)), consists of Q complex chips c_(q) ^((k)) of durationT_(c), where T_(b)=T_(c)/Q. Each data field of each burst is filled by achip sequence of length N×Q. Q is the spreading factor. Although thefollowing discussion uses a uniform spreading factor for all the Kbursts, it is also readily extendable for variable spreading factors forthe bursts. After modulating the data with their respective codes, thebursts are typically passed through a transmitter (TX) filter for pulseshaping. The receiving antenna array has P antenna elements.

The K signal bursts pass through K×P linearly independent radio channelshaving time-variant complex impulse responses, {tilde over (h)}^((k,p)),where k=1, 2, . . . , K and p=1, 2, . . . , P. {tilde over (h)}^((k,p))represents the connection of a transmitter k with an antenna element p.These channel output sequences of K bursts are superposed into Preceived sequences at each antenna element. Each superposed sequence isfiltered by the receiver (RX) filter for band limitation and noisesuppression and sampled at the chip rate 1/T_(c). The discrete channelimpulse responses h^((k,p)) for each transmitter and each antennaelement is represented as a vector per Equation 4.a. h ^((k,p))=(h ₁ ^((k,p)) h ₂ ^((k,p)) . . . h _(W) ^((k,p)))^(T),b. where k=1, 2, . . . , K, p=1, 2, . . . , P and w=1, 2, . . . , W  c.Equation 4

W is the length of the impulse response. Each of the W complex samples,h_(w) ^((k,p)), is taken at the chip rate 1/Tc, where W>T_(b). However,this approach can be readily extended to multiple chip rate sampling.Since W may be greater than T_(b), inter-symbol interference (ISI) maybe present. Typically, the channel impulse responses, h^((k,p)), isestimated using a reference sequence, such as a midamble sequences. Thesymbol responses b^((k,p)) for each burst and each antenna are perEquation 5.b ^((k,p))=(b ₁ ^((k,p)) b ^((k,p)) . . . b _(Q+w−1) ^((k,p)))^(T) ≡h^((k,p)) c ^((k)),a. where k=1, 2, . . . , K, p=1, 2, . . . , P and l=1, 2, . . . ,Q+W−1  b. Equation 5

The symbol responses, b^((k,p)), have a length of Q+W−1 chips andrepresent the tail of chips left by a unit symbol.

Prior to processing each data field, the effect of the midamble on thedata field is canceled using a midamble cancellation algorithm. At eachantenna element, the received sequence, r^((p)), where p=1, 2, . . . ,P, is of length (N Q+W−1). Each r^((p)) is effectively a sum of the Kbursts and a noise sequence per Equation 6.a. n ^((p))=(n ₁ ^((p)) n ₂ ^((p)) . . . n _(NQ+W−1) ^((p)))^(T),b. where p=1, 2, . . . , P and i=1, 2, . . . , (NQ+W−1)  c. Equation 6

The zero mean and covariance matrix is per Equation 7.R _(n) ^((p)(p)) =E{n ^((p)) n ^((p)) ^(H) }, where p=1, 2, . . . ,P  Equation 7

The transfer system matrix for each burst as received over each antennaelement is A^((k,p)) and is of size (N Q+W−1)×N. The transfer systemmatrix, A^((k,p)), is a convolution of the transmitted burst with thechannel response, h^((k,p)). Each element of the transfer system matrix,(A_(ij) ^((k,p))), is per Equation 8. $\quad\begin{matrix}{{{a.\quad A^{({k,p})}} = \left( A_{ij}^{({k,p})} \right)},{{{where}\quad k} = 1},2,\ldots\quad,K,{p = 1},2,\ldots\quad,P,} & {{Equation}\quad 8} \\{{{b.\quad i} = 1},2,\ldots\quad,{{\left( {{N\quad Q} + W - 1} \right)\quad{and}\quad j} = 1},2,\ldots\quad,N} & \quad \\{{{c.\quad{where}}\quad A_{{{Q{({n - 1})}} + l},n}^{({k,p})}} = \left\{ {\begin{matrix}\begin{matrix}{{{b_{l}^{({k,p})}\quad{for}\quad k} = 1},2,\ldots\quad,K} \\{{p = 1},2,\ldots\quad,P} \\{{l = 1},2,\ldots\quad,{Q + W - 1}} \\{{n = 1},2,\ldots\quad,N}\end{matrix} & \quad \\{0\quad{otherwise}} & \quad\end{matrix}{d.}} \right.} & \quad\end{matrix}$

The (N Q+W−1)×KN transfer system matrix A^((p)) for antenna p is perEquation 9.a. A^((p))=[A^((1,p)) A^((2,p)) . . . A^((K,p))], where k=1, 2, . . . ,K and p=1, 2, . . . , P  b. Equation 9

The P (N Q+W−1)×N transfer system matrix A^((k)) for burst k is perEquation 10. $\begin{matrix}{{A^{(k)} = \left\lbrack {A^{{({k,1})}^{T}}A^{{({k,2})}^{T}}\quad\cdots\quad A^{{({k,P})}^{T}}} \right\rbrack^{T}},{{{where}\quad k} = 1},2,\ldots\quad,{{K\quad{and}{\quad\quad}p} = 1},2,\ldots,P} & {{Equation}\quad 10}\end{matrix}$

The received sequence r^((p)) at antenna p is per Equation 11.$\begin{matrix}\begin{matrix}{r^{(p)} = \left( {r_{1}^{(p)}r_{2}^{(p)}\quad\cdots\quad r_{{NQ} + W - 1}^{(p)}} \right)^{T}} \\{= {{{A^{(p)}d} + n^{(p)}} = {{\sum\limits_{k = 1}^{K}\quad{A^{({k,p})}d^{(k)}}} + n^{(p)}}}}\end{matrix} & {{Equation}\quad 11}\end{matrix}$

The overall data symbol vector is per Equation 12. $\begin{matrix}\begin{matrix}{d = \left( {d^{{(1)}^{T}}d^{{(2)}^{T}}\quad\cdots\quad d^{{(k)}^{T}}} \right)^{T}} \\{= \left( {d_{1}d_{2}\quad\cdots\quad d_{K\quad N}} \right)^{T}}\end{matrix} & {{Equation}\quad 12}\end{matrix}$

The components of d are per Equation 13.d _(N(K−1)+n) =d _(n) ^((k)), where k=1, 2, . . . , K and n=1, 2, . . ., N.  Equation 13

The P (NQ+W−1)×KN overall transfer system matrix A is per Equation 14.$\begin{matrix}{{{a.\quad A} = \left( {A^{{(1)}^{T}}\quad A^{{(2)}^{T}}\quad\cdots\quad A^{{(P)}^{T}}} \right)^{T}}\quad{b.}} & {{Equation}\quad 14}\end{matrix}$

The overall noise vector n is per Equation 15. $\begin{matrix}\begin{matrix}{n = \left( {n^{{(1)}^{T}}n^{{(2)}^{T}}\quad\cdots\quad n^{{(P)}^{T}}} \right)^{T}} \\{= \left( {n_{1}n_{2}\quad\cdots\quad n_{P{({{N\quad Q} + W - 1})}}} \right)^{T}}\end{matrix} & {{Equation}\quad 15}\end{matrix}$

The components of n are per Equation 16.n _((NQ+W−1)(P−1)+i) =n _(i) ^((p)), where p=1, 2, . . . , P and i=1, 2,. . . , (NQ+W−1)  Equation 16

The covariance matrix of the total noise vector n is per Equation 17.$\begin{matrix}\begin{matrix}{R_{n} = {E\left\{ {n\quad n^{H}} \right\}}} \\{= \begin{bmatrix}R_{n}^{{(1)}\quad{(1)}} & R_{n}^{{(1)}\quad{(2)}} & \cdots & R_{n}^{{(1)}\quad{(P)}} \\R_{n}^{{(2)}\quad{(1)}} & R_{n}^{{(2)}\quad{(2)}} & \cdots & R_{n}^{{(2)}\quad{(P)}} \\\vdots & \vdots & ⋰ & \vdots \\R_{n}^{{(P)}\quad{(1)}} & R_{n}^{{(P)}\quad{(2)}} & \cdots & R_{n}^{{(P)}\quad{(P)}}\end{bmatrix}}\end{matrix} & {{Equation}\quad 17} \\\begin{matrix}{{{{a.\quad{where}}\quad R_{n}^{{(i)}{(j)}}} = {E\left\{ {n^{(i)}n^{{(j)}^{H}}} \right\}}},} \\{{{{where}\quad i} = 1},2,\ldots\quad,{{P\quad{and}\quad j} = 1},2,\ldots\quad,P}\end{matrix} & \quad \\{b.} & \quad\end{matrix}$

The overall received sequence is represented per Equation 18.$\begin{matrix}\begin{matrix}{r = \left( {r^{{(1)}^{T}}r^{{(2)}^{T}}\quad\cdots\quad r^{{(P)}^{T}}} \right)^{T}} \\{= \left( {r_{1}r_{2}\quad\cdots\quad r_{P{({{N\quad Q} + W - 1})}}} \right)^{T}} \\{= {{A\quad d} + n}}\end{matrix} & {{Equation}\quad 18}\end{matrix}$

The components of r are per Equation 19.r _((NQ+W−1))(P−1)+i=r _(i) ^((P)), where p=1, 2, . . . , P and i=1, 2,. . . , (NQ+W−1)  Equation 19

The overall received sequence r is per Equation 20. $\begin{matrix}\begin{matrix}{r = {{\sum\limits_{k = 1}^{K}\quad r^{(k)}} + n}} \\{= {{\sum\limits_{k = 1}^{K}\quad{A^{(k)}d^{(k)}}} + n}}\end{matrix} & {{Equation}\quad 20}\end{matrix}$

r^((k))=A^((k))d^((k)) represents the contribution of user k's signal inthe received sequence. The overall received vector r is preferablyprocessed by a GSIC using the block linear equalizer in order todetermine the continuous valued estimates {circumflex over (d)}, perEquation 21. $\begin{matrix}\begin{matrix}{\hat{d} = \left( {{\hat{d}}^{{(1)}^{T}}{\hat{d}}^{{(2)}^{T}}\quad\cdots\quad{\hat{d}}^{{(K)}^{T}}} \right)^{T}} \\{= \left( {{\hat{d}}_{1}{\hat{d}}_{2}\quad\cdots\quad{\hat{d}}_{K\quad N}} \right)^{T}}\end{matrix} & {{Equation}\quad 21}\end{matrix}$

Two approaches to using GSIC use block linear equalizers with receptiondiversity, although others may be used. One approach uses a zero forcing(ZF) criterion and another uses a minimum mean squared error (MMSE)criterion.

For the following, the additive noise is assumed to be spatially andtemporally white and the covariance matrix of the overall noise vectoris R_(n)=σ² I. σ² is the variance of the additive noise and I is theidentity matrix with size K N×K N. With reception diversity, the ZF-BLEcan be derived by minimizing the quadratic cost function J({circumflexover (d)}_(ZF)), per Equation 22.J({circumflex over (d)} _(ZF))=(r−A{circumflex over (d)}_(ZF))^(H)(r−A{circumflex over (d)} _(ZF))  Equation 22

{circumflex over (d)}_(ZF) is the continuous valued estimates of d and“−1” denotes the matrix inverse. The minimum of J({circumflex over(d)}_(ZF)) leads to the continuous valued and unbiased estimate{circumflex over (d)}_(ZF), per Equation 23. $\begin{matrix}\begin{matrix}{{\hat{d}}_{ZF} = {\left( {A^{H}A} \right)^{- 1}A^{H}r}} \\{= {d + {\left( {A^{H}A} \right)^{- 1}A^{H}n}}}\end{matrix} & {{Equation}\quad 23}\end{matrix}$

The MMSE-BLE minimizes the quadratic cost function J({circumflex over(d)}_(MMSE)), per Equation 24.J({circumflex over (d)} _(MMSE))=E{({circumflex over (d)} _(MMSE)−d)^(H)({circumflex over (d)} _(MMSE) −d)}  Equation 24

{circumflex over (d)}_(MMSE) is the continuous valued estimates of{circumflex over (d)}. With the covariance matrix of data symbolsR_(d)E{dd^(H)}=I and the covariance matrix of the overall backgroundnoise vector R_(n)=σ² I, the minimum of J({circumflex over (d)}_(MMSE))leads to the continuous valued estimate {circumflex over (d)}_(MMSE),per Equation 25.{circumflex over (d)} _(MMSE)=(A ^(H) A+σ ² I)⁻¹ A ^(H) r  Equation 25

I denotes the K N×K N identity matrix. Since A^(H) A is a banded blockToeplitz matrix, one approach to solve for the data vector uses anapproximate Cholesky formulation. The Cholesky formulation reduces thecomplexity with negligible loss in performance as compared to an exactsolution.

Preferably, to reduce the complexity and to remove ISI and multipleaccess interference (MAI), simultaneously, BLEs and GSIC are combined(GSIC-BLE). In GSIC-BLE, K bursts are divided into a small group,preferably, according to the received power. Typically, bursts havingroughly same received power get grouped together. Bursts of roughly thesame power are bursts that have a combined power as received over the Pantenna elements of equivalent power.

In each interference cancellation stage, GSIC-BLE considers the ISI andMAI of only a subset (group) of the K bursts, and jointly detects thedata symbols of this group. The detected symbols of this group are usedto generate MAI that this group imparts on the other groups forsubsequent stages. This MAI is removed using interference cancellation.If the group size is chosen to be K, the GSIC-BLE becomes a single userBLE. All of the data is determined in one step.

As a result, the grouping threshold provides a trade-off betweencomplexity and performance. In the extreme, each K burst can be assignedits own stage. This approach provides the lowest complexity. Conversely,all K bursts can be assigned to a single stage, having the highestcomplexity.

FIG. 4 is a flow chart of GSIC-BLE with reception diversity. In GSIC-BLEwith reception diversity, preferably, all bursts are ordered by thestrength of their received power or amplitude, with burst 1 being thestrongest, step 50. Such an ordering can be based upon either an aprioriknowledge at the receiver or by other estimation schemes commonlyemployed in the context of SIC or MUD receivers, such as burst-specificchannel estimation from a burst-specific training sequence, bank ofmatched filters, etc. In one implementation, using the known channel,the descending order can be decided per Equation 25. $\begin{matrix}{{\sum\limits_{p = 1}^{p}{h^{{({k,p})}^{H}}h^{({k,p})}}},{{{where}\quad k} = 1},2,\ldots\quad,K} & {{Equation}\quad 25}\end{matrix}$

Using the list of order, GSIC-BLE divides bursts that have roughly thesame power, i.e., within a certain threshold of each other, into Ggroups, step 52. The groups are arranged in descending order of theirreceived power. The order can be represented as i=1 . . . G. n_(i) isthe number of bursts in the i^(th) group, such as${\sum\limits_{i = 1}^{G}n_{i}} = {K.}$The receiver consists of G stages. Initially, a joint detection isstarted with group, i=1.

For each group, one groupwise BLE matrix is per Equation 26 for aZF-BLE.M _(g,ZF) ^((i))=(A _(g) ^((i)) ^(H) A _(g) ^((i)) A _(g) ^((i)) ^(H) ,where i=1, 2, . . . , G  Equation 26

The second groupwise BLE matrix is per Equation 27 for MMSE-BLE.$\begin{matrix}\begin{matrix}{{M_{g,{MMSE}}^{(i)} = {\left( {{A_{g}^{{(i)}^{H}}A_{g}^{(i)}} + {\sigma^{2}I_{N}}} \right)^{- 1}A_{g}^{{(i)}^{H}}}},{{{where}\quad i} = 1},2,\ldots\quad,G} \\{= {W_{g}^{(i)}M_{g,{ZF}}^{(i)}}}\end{matrix} & {{Equation}\quad 27}\end{matrix}$

The wiener estimator of the i^(th) group, W_(g) ^((i)), i=1 . . . G, isper Equation 28. $\begin{matrix}{W_{g}^{(i)} = \left( {I_{N} + {\sigma_{g}^{2}\left( {A_{g}^{{(i)}^{H}}A_{g}^{(i)}} \right)}^{- 1}} \right)^{- 1}} & {{Equation}\quad 28}\end{matrix}$

I_(N) is identity matrix of size N×N where N is the number of symbols ineach data field of each burst.

In the first stage, the transfer system matrix of the first group A_(g)⁽¹⁾ is determined. A_(g) ⁽¹⁾ is akin to the overall transfer systemmatrix A, except that it only contains the symbol responsescorresponding to bursts in the first group. In the first stage, theinput sequence for the group 1 is given by the overall received sequenceper Equation 29.x_(g) ⁽¹⁾=r  Equation 29

To remove the ISI, MAI, and the near-far effect of bursts in the firstgroup, a multiuser BLE (ZF-BLE or MMSE-BLE) with A_(g) ⁽¹⁾ is performed.The soft decision symbols for the group 1 d_(g,soft) ⁽¹⁾ are obtainedper Equation 30, step 54.{circumflex over (d)}_(g,soft) ⁽¹⁾=M_(g) ⁽¹⁾r  Equation 30

where M_(g) ^((i)), i=1, 2, . . . , G, can be either M_(g,ZF) ^((i)) orM_(g,MMSE) ^((i)).

{circumflex over (d)}_(g,soft) ⁽¹⁾ is a continuous valued estimator ofd_(g) ^((i)) that represents the sequence of information bearing symbolscarried by all bursts in the first group. Based on {circumflex over(d)}_(g,soft) ⁽¹⁾, hard decisions are performed to form {circumflex over(d)}_(g,hard) ⁽¹⁾, step 56. Using the hard decision variable {circumflexover (d)}_(g,soft) ⁽¹⁾, the contribution {circumflex over (r)}_(g) ⁽¹⁾of the first group to r is estimated per Equation 31, step 58.$\begin{matrix}\begin{matrix}{{\hat{r}}_{g}^{(1)} = \begin{bmatrix}{\hat{r}}_{g}^{{({1,1})}^{T}} & {\hat{r}}_{g}^{{({1,2})}^{T}} & \ldots & {\hat{r}}_{g}^{{({1,P})}^{T}}\end{bmatrix}^{T}} \\{= {A_{g}^{(1)}{\hat{d}}_{g,{hard}}^{(1)}}}\end{matrix} & {{Equation}\quad 31}\end{matrix}$

{circumflex over (r)}_(g) ^((1,p)) p=1, 2, . . . , P, is thecontribution of the first group to the received sequence at antenna p.For the second stage, the interference-corrected input sequence isobtained by canceling out this MAI from the overall received sequence,per Equation 32. $\begin{matrix}\begin{matrix}{x_{g}^{(2)} = \begin{bmatrix}{\overset{\sim}{r}}_{g}^{{({2,1})}^{T}} & {\overset{\sim}{r}}_{g}^{{({2,2})}^{T}} & \ldots & {\overset{\sim}{r}}_{g}^{{({2,P})}^{T}}\end{bmatrix}^{T}} \\{= {x_{g}^{(1)} - {\hat{r}}_{g}^{(1)}}} \\{= {\left( {I_{g} - \Phi_{g}^{(1)}} \right)r}}\end{matrix} & {{Equation}\quad 32}\end{matrix}$

Φ_(g) ^((i)) is per Equation 33 for a ZF-BLE.Φ_(g) ^((i)) ≡A _(g) ^((i))(A _(g) ^((i)) ^(H) A _(g) ^((i)))⁻¹ A _(g)^((i)) ^(H)   Equation 33

Φ_(g) ^((i)) is per Equation 34 for a MMSE-BLE.Φ_(g) ^((i)) ≡A _(g) ^((i))(A _(g) ^((i)) ^(H) A _(g) ^((i))σ² I)⁻¹ A_(g) ^((i)) ^(H)   Equation 34

I_(g) is an identity matrix of size (NQ+W−1)×(NQ+W−1). {tilde over(r)}_(g) ^((2,p)) is a new interference-corrected input sequence forantenna p by subtracting {circumflex over (r)}_(g) ^((1,p)) from theinterference-corrected vector {tilde over (r)}_(g) ^((1,p)) of the firststage input sequence for antenna p (the received sequence at antenna p)

For subsequent stages, such as an i^(th) stage, a newinterference-corrected input sequence is determined by subtracting theMAI of the previous group from the interference-corrected input sequenceof the previous stage, x_(g) ^((i-1)), per Equation 35. $\begin{matrix}\begin{matrix}{x_{g}^{(i)} = {x_{g}^{({i - 1})} - {\hat{r}}_{g}^{({i - 1})}}} \\{= {\left( {I_{g} - \Phi_{g}^{({i - 1})}} \right)x_{g}^{({i - 1})}}} \\{= {\left\lbrack {\prod\limits_{j = 1}^{i - 1}\left( {I_{g} - \Phi_{g}^{(j)}} \right)} \right\rbrack r}}\end{matrix} & {{Equation}\quad 35}\end{matrix}$

The product matrices are per Equation 36. $\begin{matrix}{{\prod\limits_{j = a}^{b}X_{i}} = \left\{ \begin{matrix}X_{b} & X_{b - 1} & \ldots & X_{a + 1} & {X_{a},} & {{{if}\quad a} \leq b} \\I & \quad & \quad & \quad & \quad & {{{if}\quad a} > b}\end{matrix} \right.} & {{Equation}\quad 36}\end{matrix}$

Similar to the first stage, x_(g) ^((i)) consists of {tilde over(r)}^((i,p)), p=1, 2, . . . , P for each antenna. Single user ormultiuser BLE is performed to get rid of the MAI, ISI and the near-farproblem of the i^(th) group itself. The soft decision symbols arerepresented as per Equation 37, step 60.{circumflex over (d)}_(g,soft) ^((i))=M_(g) ^((i))x_(g) ^((i))  Equation37

Using the soft decision symbols, hard decision symbols {circumflex over(d)}_(g,hard) ^((i)) are produced by making hard decisions, step 62. Thehard symbols are used to generate the contribution {circumflex over(r)}_(g) ^((i)) of the i^(th) group in r, per Equation 38, step 64.{circumflex over (r)}_(g) ^((i))=A_(g) ^((i)){circumflex over(d)}_(g,soft) ^((i))  Equation 38

Similar to the first stage, {circumflex over (r)}_(g) ^((i)) consists of{circumflex over (r)}_(g) ^((i,p)), p=1, 2, . . . , P for each antenna.For the next stage, the interference-corrected input sequence isobtained by subtracting this MAI from the i^(th) input sequence, as perEquation 39, step 66. $\begin{matrix}\begin{matrix}{x_{g}^{({i + 1})} = {x_{g}^{(i)} - {\hat{r}}_{g}^{(i)}}} \\{= {\left\lbrack {\prod\limits_{j = 1}^{i}\left( {I_{g} - \Phi_{g}^{(j)}} \right)} \right\rbrack r}}\end{matrix} & {{Equation}\quad 39}\end{matrix}$

In the last stage, the input sequence becomes Equation 40.$\begin{matrix}\begin{matrix}{x_{g}^{(G)} = {x_{g}^{({G - 1})} - {\hat{r}}_{g}^{({G - 1})}}} \\{= {\left\lbrack {\prod\limits_{j = 1}^{G - 1}\quad\left( {I_{g} - \Phi_{g}^{(j)}} \right)} \right\rbrack r}}\end{matrix} & {{{Equation}\quad 40}\quad}\end{matrix}$

By performing single or multiuser BLE, the soft decision symbol isobtained as per Equation 41.{circumflex over (d)}_(g,soft) ^((G))=M_(g) ^((G))x_(g) ^((G))  Equation41

The hard decision symbols {circumflex over (d)}_(g,hard) ^((G)) of thefinal stage are obtained from these soft decision symbols using harddecisions. By considering each stage as a linear filtering of thereceived sequence, the linear filter e_((g)) ^((i)), i=1 . . . G foreach stage is per Equation 42. $\begin{matrix}{e_{g}^{(i)} = {\left\lbrack {\prod\limits_{j = 1}^{i - 1}\quad\left( {I - \Phi_{g}^{(j)}} \right)} \right\rbrack^{H}\quad M_{g}^{{(i)}^{H}}}} & {{Equation}\quad 42}\end{matrix}$

The soft decision symbol at each stage is per Equation 43.$\begin{matrix}\begin{matrix}{{\hat{d}}_{g,{soft}}^{(i)} = {{M_{g}^{(i)}\left\lbrack {\prod\limits_{j = 1}^{i - 1}\quad\left( {I - \Phi_{g}^{(j)}} \right)} \right\rbrack}r}} \\{= {e_{g}^{{(i)}^{H}}r}} \\{= {{{{diag}\left( {e_{g}^{{(i)}^{H}}A} \right)}d} + {{\overset{\_}{diag}\left( {e_{g}^{{(i)}^{H}}A} \right)}d} + {e_{g}^{{(i)}^{H}}n}}}\end{matrix} & {{Equation}\quad 43}\end{matrix}$

diag(X) represents a diagonal matrix containing only the diagonalelements of the matrix X. diag(X) represents a matrix with zero diagonalelements, containing all but the diagonal elements of X.

In Equation 43, the first term represents the desired symbols of thei^(th) group, the second term represents the ISI and MAI term of thei^(th) group, and the last term is the background noise term at theoutput of the i^(th) stage. The first term is a vector whose j^(th)component is the j^(th) component of the transmitted data symbol vectorof the i^(th) group d_(g) ^((i)), multiplied by a scalar. The secondterm due to the MAI and ISI is a vector whose j^(th) component is aweighted sum of all other transmitted symbols in the overall transmitteddata symbol vector d. The correlation of the background noise term isgiven by its covariance matrix e_(g) ^((i)) ^(H) R_(n) e_(g) ^((i)),where R_(n) is the covariance of the additive noise in the overallreceived sequence. The SINR (Signal to Interference and Noise Ratio) perdata symbol at the output of each stage is per Equation 44.$\begin{matrix}{{\gamma_{n}^{(k)} = \frac{E\left\{ {d_{n}^{(k)}}^{2} \right\}\left( \left\lbrack F_{g}^{(i)} \right\rbrack_{j,j} \right)^{2}}{\begin{matrix}{\left\lbrack {F_{g}^{(i)}R_{d}F_{g}^{{(i)}^{H}}} \right\rbrack_{j,j} - {2\quad{Re}{\left\{ \left\lbrack {F_{g}^{(i)}R_{d}} \right\rbrack_{j,j} \right\}\left\lbrack F_{g}^{(i)} \right\rbrack}_{j,j}} +} \\{{E\left\{ {d_{n}^{(k)}}^{2} \right\}\left( \left\lbrack F_{g}^{(i)} \right\rbrack_{j,j} \right)^{2}} + \left\lbrack {e_{g}^{(i)}R_{n}e_{g}^{{(i)}^{H}}} \right\rbrack_{j,j}}\end{matrix}}},} & {{Equation}\quad 44} \\{{{a.\quad{where}}\quad F_{g}^{(i)}} = {e_{g}^{{(i)}^{H}}A}} & \quad \\{b.\quad\begin{matrix}{{j = {n + {N\left( {k - 1} \right)}}},} & {{i = 1},2,\ldots\quad,G,} \\{{k = 1},2,{\ldots\quad.n_{i}},} & {{n = 1},2,\ldots\quad,N}\end{matrix}} & \quad \\{c.} & \quad\end{matrix}$

Re{ } denotes the real part. [X]_(j,j) denotes the element in the j^(th)row and the j^(th) column of the matrix X. R_(d)=E{dd^(H))} is thecovariance matrix of d.

In simulations, full BLEs FBLEs (BLEs having only a single stage) showbetter performance than GSIC-BLEs. When considering the coding gain fora 1% to 10% uncoded Bit Error Rate (BER), the performance of GSIC-BLE isclose to the FBLEs.

The GSIC-BLE is also suited for the multi-code scenario where some orall users transmit multiple codes. Multi-codes from the same user can begrouped together and multiuser BLE is performed on each group. The MAIbetween groups is canceled by SIC. GSIC-BLE achieves better performancethan conventional SIC in two ways. First, unlike conventional SIC, itmaintains performance in the absence of a near-far effect by performingmultiuser BLE of bursts received with similar power. Second, unlikeconventional RAKE-based SIC receivers, it better accounts for the ISI ofeach burst via multiuser BLE of each group. The optimal mitigation ofISI leads to a more effective cancellation of MAI between groups,especially in channels with large delay spreads.

GSIC-BLE typically achieves a complexity that varies linearly with thenumber of bursts, K, which is substantially less than that of FBLE.Since this case accounts for the ISI in each burst, it potentially leadsto a better performance than SIC receivers based on a RAKE. Thisperformance advantage increases in channels with large delay spreads,i.e., when the ISI is significant. Even for large delay spread channels,a near-far effect of the order of 0 to 2 dB between bursts appears to beenough to achieve a performance comparable to FBLE.

FIG. 5 is a simplified block diagram of a GSIC-BLE for use with receivediversity. The received vector, {tilde over (r)}_(g) ^((1,1)) to {tildeover (r)}^((1,P)), from each of the P antenna elements are input intothe GSIC-BLE. A group 1 matched filter 70 match filters, A_(g) ⁽¹⁾ ^(H)x_(g) ⁽¹⁾, the received vectors for group 1. A result of the matchedfiltering, y_(g) ⁽¹⁾, is processed by a BLE, such as a ZF, (A_(g) ⁽¹⁾^(H) A_(g) ⁽¹⁾)⁻¹ y_(h) ⁽¹⁾, or MMSE, (A_(g) ⁽¹⁾ ^(H) A_(g) ⁽¹⁾+σ²I)⁻¹y_(g) ⁽¹⁾. A result of the BLE 72, {circumflex over (d)}_(soft) ⁽¹⁾, isconverted to hard symbols, {circumflex over (d)}_(hard) ⁽¹⁾ by a soft tohard decision device 74. An interference correction device 76 uses thehard symbols, {circumflex over (d)}_(hard) ⁽¹⁾ to produce a vector,{circumflex over (r)}_(g) ^((1,1)) to {circumflex over (r)}_(g)^((1,P)), for each antenna representing the contribution of group 1 tothat antenna's received vector. For each antenna, a subtractor 92 ₁ to92 _(P) subtracts the contribution from group 1, {circumflex over(r)}_(g) ^((1,1)) to {circumflex over (r)}_(g) ^((1,P)), from thereceived vectors, {tilde over (r)}_(g) ^((1,1)) to {tilde over (r)}_(g)^((1,P)), to produce an interference cancelled vector, {tilde over(r)}_(g) ^((2,1)) to {tilde over (r)}^((2,P)), for each antenna.

A group 2 matched filter 78 match filters, A_(g) ⁽²⁾ ^(H) x_(g) ⁽²⁾, theinterference cancelled vectors. A result of the matched filtering, y_(g)⁽²⁾, is processed by a BLE 80, such as a ZF, (A_(g) ⁽²⁾ ^(H) A_(g)⁽²⁾)⁻¹ y_(g) ⁽²⁾, or MMSE, (A_(g) ² ^(H) A_(g) ⁽²⁾+σ²I)⁻¹ y_(g) ⁽²⁾. Aresult of the BLE, {circumflex over (d)}_(soft) ⁽²⁾, is converted tohard symbols, {circumflex over (d)}_(hard) ⁽²⁾, by a soft to harddecision device 82. An interference correction device 84 uses the hardsymbols, {circumflex over (d)}_(hard) ⁽²⁾, to produce a vector,{circumflex over (r)}_(g) ^((2,1)) to {circumflex over (r)}_(g) ^((2,P))for each antenna representing the contribution of group 2 to thatantenna's received vector. For each antenna, a subtractor 94 ₁ to 94_(P) subtracts the contribution from group 2, {circumflex over (r)}_(g)^((2,1)) to {circumflex over (r)}^((2,P)), from the received vectors,{tilde over (r)}_(g) ^((2,1)) to {circumflex over (r)}_(g) ^((2,P)), toproduce an interference cancelled vector, {tilde over (r)}_(g) ^((3,1))to {tilde over (r)}^((3,P)), for each antenna.

The estimation of data for the remaining groups, groups 3 to G−1, andinterference cancellation is successively performed until the finalgroup G. For group G, a group G matched filter 86 match filters, A_(g)^((G)) ^(H) x_(g) ^((G)), the interference cancelled vectors. A resultof the matched filtering, y_(g) ^((G)), is processed by a BLE 88, suchas a ZF, (A_(g) ^((G)) ^(H) A_(g) ^((G)))⁻¹ y_(g) ^((G)), or MMSE,(A_(g) ^((G)) ^(H) A_(g) ^((G))+σ²I)⁻¹ y_(g) ^((G)). A result of theBLE, {circumflex over (d)}_(soft) ^((G)), is converted to hard symbols,{circumflex over (d)}_(hard) ^((G)), by a soft to hard decision device90.

1. A base station (BS) for transmitting and receiving a plurality ofdata signals using an antenna array, the BS comprising: a transmitterfor transmitting data signals over a shared spectrum, the transmitterincluding, a data generator for generating reference data signals to becommunicated over a reference channel, a spreading and modulation devicefor spreading reference data into a communication burst, a modulator formodulating the communication burst into a radio frequency (RF) signal,and an antenna for radiating the RF signal through a wireless radiochannel to a receiver; and a receiver for receiving the RF signal, thereceiver including, an antenna array having a plurality of antennaelements, a plurality of demodulators, each demodulator corresponding toone of the plurality of antenna elements, wherein each demodulatordemodulates the RF signal received by the corresponding one of theplurality of antenna elements to produce baseband signals, a channelestimation device for providing channel information based on trainingsequences components in the baseband signals, and a group wisesuccessive interference cancellation (GSIC) joint detection (JD) device,for estimating the transmitted reference data signals as either hard orsoft symbols.
 2. The BS of claim 1 wherein the communication burst istime multiplexed with a training sequence in appropriate assigned timeslots and codes.
 3. The BS of claim 1 wherein the communication burst isan almost continuous global pilot.
 4. The BS of claim 1 wherein themodulator uses direct phase shift keying (DPSK).
 5. The BS of claim 1wherein the modulator uses quadrature phase shift keying (QPSK).
 6. TheBS of claim 1 wherein the modulator uses M-ary quadrature amplitudemodulation (QAM).
 7. The BS of claim 2 wherein the communication burstincludes: a midamble; a guard period; and two data fields.
 8. The BS ofclaim 7 wherein the midamble is between the two data fields.
 9. The BSof claim 7 wherein the guard period the communication burst from a nextcommunication burst.
 10. The BS of claim 7 wherein the two data fieldsare the same length.